{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import mpl_toolkits.axisartist as AA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.genfromtxt(\"ConstVolumeIgnSolution.dat\", dtype=str)\n",
    "Header = (data[0,:]).tolist()\n",
    "solTchem = (data[1:,:]).astype(np.float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def makefigure(x, y1, y2, y3, y4, info, fs_label=16, fs_tick=14, figure_name='TempDensVelPFR' ):\n",
    "    \n",
    "    label1 = info['label1']['label']\n",
    "    label2 = info['label2']['label']\n",
    "    label3 = info['label3']['label']\n",
    "    label4 = info['label4']['label']\n",
    "    \n",
    "    ylabel1 = label1 + info['label1']['units']\n",
    "    ylabel2 = info['label2']['units']\n",
    "    \n",
    "    fig = plt.figure()\n",
    "#     host = AA.Axes(fig, [0.1, 0.1, 0.8, 0.8]) \n",
    "#     fig.add_axes(host)\n",
    "    host = fig.add_axes([0.1, 0.1, 0.8, 0.8]) \n",
    "    par1 = host.twinx()\n",
    "\n",
    "    host.set_xlabel(\"Time [s]\",fontsize=fs_label)\n",
    "    host.set_ylabel(ylabel1,fontsize=fs_label)\n",
    "    par1.set_ylabel(ylabel2,fontsize=fs_label)\n",
    "\n",
    "    p1 = host.plot(x, y1,'k-', label=label1)\n",
    "    p2 = par1.plot(x, y2,'b-', label=label2)\n",
    "    p3 = par1.plot(x, y3,'g-', label=label3)\n",
    "    p4 = par1.plot(x, y4,'-',color='r',label=label4)\n",
    "\n",
    "    host.set_yticks([1000,1500,2000,2500])\n",
    "    loc_x = info['loc_x']\n",
    "    loc_y = info['loc_y']\n",
    "    \n",
    "    par1.set_xlim(info['xlim'])\n",
    "\n",
    "    # added these three lines\n",
    "    lns = p1+p2+p3+p4\n",
    "    labs = [l.get_label() for l in lns]\n",
    "    host.legend(lns, labs, bbox_to_anchor=(loc_x, loc_y),fontsize=fs_tick,frameon=False)\n",
    "    \n",
    "    inset = fig.add_axes([info['inset_x1'], info['inset_y1'], info['inset_x2'], info['inset_y2']]) \n",
    "    inset.plot(x, y1,'k.-')\n",
    "    inset.set_yticks([])\n",
    "    par2 = inset.twinx()\n",
    "    par2.set_yticks([])\n",
    "    par2.plot(x, y2,'b.-')\n",
    "    par2.plot(x, y3,'g.-')\n",
    "    par2.plot(x, y4,'.-',color='r')\n",
    "    inset.set_xlim(info['xlim2'])\n",
    "    for tick in host.xaxis.get_major_ticks()+host.yaxis.get_major_ticks():\n",
    "        tick.label.set_fontsize(fs_tick)\n",
    "    for tick in inset.xaxis.get_major_ticks():\n",
    "        tick.label.set_fontsize(fs_tick-2)\n",
    "    for tick in par1.yaxis.get_major_ticks():\n",
    "        tick.label2.set_fontsize(fs_tick)\n",
    "\n",
    "    plt.savefig(figure_name,bbox_inches='tight')\n",
    "    return \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "CH4_indx = Header.index('CH4')\n",
    "O2_indx = Header.index('O2')\n",
    "CO_indx = Header.index('CO')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "info={}\n",
    "info['label1'] = {'label':'Temperature','units':' [K]'}\n",
    "info['label2'] = {'label': 'CH4','units':' Mass Fraction'}\n",
    "info['label3'] = {'label': 'O2','units':'  Mass Fraction'}\n",
    "info['label4'] = {'label': 'CO','units':'  Mass Fraction'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "info['loc_x'] = 0.45\n",
    "info['loc_y'] = 0.75\n",
    "info['xlim'] = [0.6,1.75]\n",
    "info['xlim2'] = [1.06,1.08]\n",
    "info['inset_x1'] = 0.55 \n",
    "info['inset_y1'] = 0.4\n",
    "info['inset_x2'] = 0.3\n",
    "info['inset_y2'] = 0.4\n",
    "\n",
    "x  = solTchem[:,1]\n",
    "y1 = solTchem[:,5]\n",
    "y2 = solTchem[:,CH4_indx]\n",
    "y3 = solTchem[:,O2_indx]\n",
    "y4 = solTchem[:,CO_indx]\n",
    "makefigure(x, y1, y2, y3, y4, info, fs_label=16, fs_tick=14, figure_name='TempMassFraction2.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "info={}\n",
    "info['label1'] = {'label':'Temperature','units':' [K]'}\n",
    "info['label2'] = {'label': 'OH','units':' Mass Fraction'}\n",
    "info['label3'] = {'label': 'H','units':'  Mass Fraction'}\n",
    "info['label4'] = {'label': 'H2','units':' Mass Fraction'}\n",
    "info['loc_x'] = 0.55\n",
    "info['loc_y'] = 0.55\n",
    "info['xlim'] = [0.7,1.5]\n",
    "info['xlim2'] = [1.06,1.08]\n",
    "info['inset_x1'] = 0.15 \n",
    "info['inset_y1'] = 0.35\n",
    "info['inset_x2'] = 0.3\n",
    "info['inset_y2'] = 0.4\n",
    "OH_indx = Header.index('OH')\n",
    "H_indx = Header.index('H')\n",
    "H2_indx = Header.index('H2')\n",
    "y1 = solTchem[:,5]\n",
    "y2 = solTchem[:,OH_indx]\n",
    "y3 = solTchem[:,H_indx]\n",
    "y4 = solTchem[:,H2_indx]\n",
    "makefigure(x, y1, y2, y3, y4, info, figure_name='TempMassFraction3.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(x,solTchem[:,Header.index('dt')],'r.-')\n",
    "plt.yscale('log')\n",
    "plt.xlim([0.7,1.6])\n",
    "plt.ylim([1e-8,2e-3])\n",
    "plt.ylabel('dt [s]',fontsize=16)\n",
    "plt.xlabel('Time [s]',fontsize=16)\n",
    "plt.xticks(fontsize=14)\n",
    "plt.yticks(fontsize=14)\n",
    "plt.savefig('dt.pdf',bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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